We initiate the study of incentives in a general machine learning framework. We focus on a game-theoretic regression learning setting where private information is elicited from mu...
Voting in uncontrolled environments, such as the Internet comes with a price, the price of having to trust in uncontrolled machines the collection of voter’s vote. An uncontrolle...
Abstract. The dependency pair technique is a powerful modular method for automated termination proofs of term rewrite systems. We first show that dependency pairs are also suitabl...
Organisational structures for multi-agent systems are usually defined independently of any spatial and temporal structure. Therefore, when the multi-agent system is situated in a ...
Abstract. We propose a new matrix learning scheme to extend Generalized Relevance Learning Vector Quantization (GRLVQ). By introducing a full matrix of relevance factors in the dis...